1. Field of the Invention
The present invention relates to the detection of an object and more particularly to a method for two-dimensional detection and recognition of the object from silhouette images based on multiple projections.
2. Discussion of the Prior Art
Fast two-dimensional (2D) object detection and recognition is needed in many machine vision applications. For example, 2D object detection is often needed to detect, recognize and distinguish objects moving on a conveyor belt.
Where the objects can be characterized and distinguished based on shape, silhouette images obtained through back light illumination offer the possibility to focus merely on the object shape without being influenced by the surfaces of the objects or other reflections. As a result, a binary silhouette (e.g., black/white or 0/1) may be classified. The binary silhouette can be captured using a standard camera or a line scan camera.
Various techniques exist for the classification of silhouette images, for example, geometric moments, Fourier descriptors and Blob analysis. Geometric moments are described by S. X. Liao and M. Pawlak, “On Image-Analysis By Moments”, PAMI 18, No. 3, March 1996, pp. 254-266. A discussion of Fourier descriptors can be found in N. Kiryati, “Calculating Geometric Properties of Objects Represent by Fourier Coefficients”, CVPR 1988, pp. 641-646. M. O. Shneier described Blob analysis in “Using Pyramids to Define Local Thresholds for Blob Detection”, PAMI No. 3, May 1983, pp. 345-349. However, these methods can fail if there are multiple objects within the silhouette, particularly when two or more objects appear to touch.
Therefore, a need exists for a system and method of two-dimensional detection and recognition of an object from silhouette images based on multiple projections.